1. Field
Embodiments presented herein provide techniques for simplifying models of robots, and, in particular, for systematically deriving simplified models of humanoid robots.
2. Description of the Related Art
In humanoid robot control, simplified dynamics models are often used to represent the robot, as it is difficult to design controllers that control full dynamics models having many degrees of freedom (DOF). Typically, simplified models have fewer DOF than full models and are linearized in order to apply linear control theory. Examples of simplified models include the one-joint inverted pendulum model, the two-joint inverted pendulum model, the cart-table model, the inverted pendulum with reaction wheel, the double inverted pendulum, and the linear biped model. Conventionally, controller developers formulate these models manually based on their intuition. This approach is difficult to generalize, and it is not always clear how to determine parameters of a simplified model, or if the simplified model captures the essential dynamics of the full model. Further, model-specific programs, each of which can be employed with particular model(s), may be required to compute the state of the simplified models. For example, a one-joint inverted pendulum model may use the center-of-mass (COM) of the entire body and thus require a different program than a two joint inverted pendulum model that uses separate COMB for the upper and lower body. In addition, joints of simplified models may not correspond to physical joints, so converting between input torques of simplified models and joint torques of full models may not be straightforward, especially since no systematic approach exists for performing such a conversion.